The research proposed involves five different topics (i) the extension of tree-structured, recursive partitioning methods to the analysis of censored survival data from clinical trials or laboratory experiments; (ii) aggregated Markov models (in neurophysiology) that are crucial to the understanding of the acetylcholine receptor; (iii) the application of multivariate methods to the understanding of ocular micro-circulation and the early diagnosis of diabetes; (iv) binary regression with errors in variables and its use in evaluating burn care facilities; (v) estimation in pharmacokinetic models which arise in high dose intracavitary chemotherapy as it is administered at the UC San Diego Cancer Center.